In a typical primary placement with a third party debt collection agency, fewer than 40% of accounts receive anything resembling sustained collection activity. The rest age, and while they age, collectability erodes at roughly 1% per week.
The industry has a term for this, the contingency alignment problem. Agencies operating on a contingency model rationally concentrate effort on accounts most likely to produce recoveries.
Fresh placements, elevated balances, high-contact-probability consumers get the attention, while low-balance, aged, or difficult-to-locate accounts move to the back of the queue, then drop off entirely.
The FTC's study of the debt buying industry documented the primary, secondary, and tertiary placement cascade.
Accounts go to a primary third party debt collection agency, the unrecovered balance moves to a secondary, and what remains passes to a tertiary tier at progressively higher debt collection agency fees and diminishing recovery probability.
Each handoff compounds the loss, and collectability declines sharply after the first 90 days. By 12 months past charge-off, recovery rates have fallen to roughly 25% of their initial level.
What the data also shows, and what vendor scorecards rarely capture, is that within any single placement, agencies apply their own internal prioritization. Accounts are not worked uniformly.
Contact cadences, collector assignment, and dialing intensity all follow the economics of contingency. Maximum effort goes where expected revenue per hour worked is highest. The accounts that receive that intensity are a fraction of what was placed.
Industry-standard debt collection agency fees run 15 to 25% on fresh placements under 90 days, climbing to 25 to 40% in the 6 to 12 month range and 40 to 50% on legal-track or significantly aged paper.
For a mixed-age portfolio, blended debt collection agency fees typically settle between 20 and 35%. What receives less scrutiny is their cumulative impact when measured not against gross recovered dollars, but against total face value, including the face value of accounts that never received meaningful activity.
The agency remits a check, and the rate looks within range. But the effective cost of debt collection agency fees, measured against the full recovery potential of the book and not just the portion the agency pursued, tells a materially different story.
As debt ages within the placement cycle, that calculus worsens. Fee percentages climb on older accounts precisely because recovery probability is falling, while actual collection effort per account contracts. The buyer pays more for less, on a portfolio whose recoverable value is declining weekly.
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Running first-party collection at meaningful scale required licensed infrastructure and management overhead that the economics did not support outside of the largest buyers.
The choice was between delegating to agencies and absorbing debt collection agency fees and coverage gaps, or internalizing operations at costs that rarely penciled out. AI agents alter that calculus in a way that is less incremental than categorical.
An AI agent operating across a debt portfolio has no marginal cost per contact, no economic rationale to deprioritize sub-$500 balances or 18-month aged paper, and no reason to concentrate effort on a subset of what was placed.
It works the full book, every account on a cadence calibrated to its risk profile, before any placement decision is made. Every interaction is documented, compliance is verifiable on every call, not on a statistical sample.
Every conversation is recorded, transcribed, and reviewed against FDCPA requirements and internal protocol. The posture shifts from reactive to proactive, with call-level visibility before any dispute materializes rather than surfacing problems through CFPB complaints or periodic audits after the fact.
Contact rates by segment, objection patterns, right-party contact performance, and payment intent signals accumulate as proprietary intelligence on how the portfolio behaves. Agencies provide reporting, while AI agents produce a continuous, compounding signal that informs collection strategy and future portfolio decisions.
When accounts go to agencies, they arrive with a documented history of contact attempts, consumer engagement data, and pre-qualification for the type of work agencies perform well. The placement is more precise, the paper is better characterized, and debt collection agency fees apply only to the work that genuinely requires them.
Before the next agency performance conversation, pull these numbers. If most of them are unavailable, that is itself informative.
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